6239 - 自然語言處理：理論、模型與應用

Natural Language Processing: Theory, Models, and Applications

教育目標 Course Target

本課程介紹自然語言處理（NLP）的核心理論、演算法與實務應用，從傳統文字處理與統計模型，逐步延伸至深度學習與大型語言模型（LLM）。課程內容涵蓋文字表示、語言模型、序列建模、語意理解、文本生成與實際應用案例，並搭配 Python 與主流 NLP 套件進行實作，培養學生分析、設計與應用自然語言系統的能力。

This course introduces the core theories, algorithms and practical applications of natural language processing (NLP), from traditional word processing and statistical models to gradually extending to deep learning and large language models (LLM). The course content covers text representation, language model, sequence modeling, semantic understanding, text generation and practical application cases, and is implemented with Python and mainstream NLP packages to cultivate students' ability to analyze, design and apply natural language systems.

參考書目 Reference Books

自行提供上課簡報
Benjamin Bengfort , Rebecca Bilbro , Tony Ojeda. Applied Text Analysis with Python: Enabling Language-Aware Data Products with Machine Learning, 2018

Provide class presentations by yourself
Benjamin Bengfort , Rebecca Bilbro , Tony Ojeda. Applied Text Analysis with Python: Enabling Language-Aware Data Products with Machine Learning, 2018

評分方式 Grading

評分項目
Grading Method		 配分比例
Percentage		 說明
Description
期中考
midterm exam
 25
期末報告
Final report
 40
出席
Attend
 15
作業課堂討論
Homework class discussion
 20

授課大綱 Course Plan

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課程資訊 Course Information

基本資料 Basic Information
  • 課程代碼 Course Code: 6239
  • 學分 Credit: 0-3
  • 上課時間 Course Time:
    Tuesday/6,7,8[M217]
  • 授課教師 Teacher:
    賴翌維
  • 修課班級 Class:
    資管系3,4,碩1,2
  • 選課備註 Memo:
    電腦教室
選課狀態 Enrollment Status
目前選課人數 Current Enrollment: 7 人
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